/// <summary>
/// Creates a cost system. Assigns resources to pools and selects
/// drivers for each pool.
/// </summary>
/// <param name="ip">An input parameters object.</param>
/// <param name="firm">The firm upon which this cost system is based.</param>
/// <param name="a">The number of activity cost pools to form.</param>
/// <param name="p">A flag indicating method for assigning resources to cost pools.
/// See input file cheat sheet for details.</param>
/// <param name="r">A flag indicating which resources in the pools
/// will be used to form drivers. See input file cheat sheet for details.</param>
public CostSys(
InputParameters ip,
Firm firm,
int a,
int p,
int r)
{
this.firm = firm;
RowVector RCC = firm.Initial_RCC;
int[] RANK = firm.Initial_RANK;
SymmetricMatrix CORR = firm.PEARSONCORR;
this.a = a;
this.p = p;
this.r = r;
if (a != 1)
{
#region Code shared in flowchart 6.1, 6.2, and 6.3
// Segregate resources into big ones that will each
// seed a pool, and miscellaneous resources.
// The first (a-1) resources get their own pools.
List <int> bigResources = RANK.Take(a - 1).ToList();
List <int> miscResources = RANK.Skip(a - 1).ToList();
// Create the set B and initialize the first
// elements with the big pool resources.
// Seeding big resources
// Take each resource from bigPools, ane make it into a list
// of length 1. Convert to an array of lists, and assign to B.
B = bigResources.Select(elem => new List <int> {
elem
}).ToArray();
// Increase the length by 1, to make room for the miscellaneous
// pool.
Array.Resize(ref B, B.Length + 1);
B[B.Length - 1] = new List <int>();
#endregion
// p == 0:
// Seed (a-1) pools with the largest (a-1) resources.
// All remaining resources assigned to miscellaneous pool
if (p == 0)
{
#region Flowchart 6.1
B[a - 1] = new List <int>(miscResources);
#endregion
}
// p == 1:
// Seed acp-1 pools based on size. Check to see
// the highest correlation for the remaining resources. Assign the
// unassigned resource with the highest correlation to
// the relevant ACP. Check to see if the value of remaining
// ACP > MISCPOOLSIZE. If so, continue to find the next highest
// correlation, assign and check. When remaining value < 20%,
// then pool everything into misc.
else if (p == 1)
{
#region Flowchart 6.2
// This query iterates over miscResources. For each one, it
// computes the correlation with every bigResource, and forms
// a record {smallResourceIndex, index of big pool (in B), correlation }.
// Order this list of records in descending order and keep the first one.
// This first one is the pool to which the small resources will be allocated
// if the correlation is sufficiently high.
var query =
miscResources.Select(smallRes => bigResources.Select((bigRes, i) => new { smallRes, BigPoolNum = i, correl = CORR[bigRes, smallRes] }).OrderByDescending(x => x.correl).First());
// Order the small resources by correlation with big resources. Thus,
// if resource 7 is most correlated with big pool resource 0 (92%),
// and resource 12 is most correlated with big pool resource 1 (83%),
// 7 will be ahead of 12 in myArray.
var myArray = query.OrderByDescending(x => x.correl).ToArray();
// The following block makes sure that at least one nonzero
// resource is allocated to the last pool. The only time this
// fails is if all miscellaneous resources are zero.
int lastResourceToAllocate;
{
// Convert each record in myArray to the value of the resource
// cost pool represented by that resource
var moo = myArray.Select(x => RCC[x.smallRes]);
// Convert each element of moo to the value of the remaining
// resources in the array at this point.
var moo2 = moo.Select((_, i) => moo.Skip(i).Sum());
List <double> ld = moo2.ToList();
// If the list contains a 0, that means there are one or
// more zero resources. Find the index of the first one,
// or if there isn't one, use the end of the array.
if (ld.Contains(0.0))
{
lastResourceToAllocate = ld.IndexOf(0.0) - 1;
}
else
{
lastResourceToAllocate = myArray.Length;
}
}
double TR = RCC.Sum();
double notYetAllocated = miscResources.Aggregate(0.0, (acc, indx) => acc + RCC[indx]);
bool cutoffReached = (notYetAllocated / TR) < ip.MISCPOOLSIZE;
for (int k = 0; (k < lastResourceToAllocate) && !cutoffReached; ++k)
{
var q = myArray[k];
if (q.correl >= ip.CC)
{
B[q.BigPoolNum].Add(q.smallRes);
miscResources.Remove(q.smallRes);
}
else
{
break;
}
notYetAllocated = miscResources.Aggregate(0.0, (acc, indx) => acc + RCC[indx]);
cutoffReached = (notYetAllocated / TR) < ip.MISCPOOLSIZE;
}
// Check if there is anything left in miscResources
// If yes, throw it in the miscellaneous pool (B.Last()).
if (miscResources.Count > 0)
{
B.Last().AddRange(miscResources);
}
// If not, remove the last allocated resource (myArray.Last())
// from the pool to which it was allocated, and place it in the
// miscellaneous pool.
else
{
var q = myArray.Last();
B[q.BigPoolNum].Remove(q.smallRes);
B.Last().Add(q.smallRes);
}
#endregion
}
// p == 2:
// Seed each of the (a-1) cost pools with the largest resources.
// Allocate the remaining resources to the (a-1) pools at random.
// However, ensure that enough resources are in the last pool.
// The fraction of resources in the last pool is MISCPOOLSIZE.
else if (p == 2)
{
#region Flowchart 6.3
double TR = RCC.Sum();
// Magnitude of resources not yet allocated
double notYetAllocated = miscResources.Aggregate(0.0, (acc, indx) => acc + RCC[indx]);
// Fraction of resources not yet allocated
double miscPoolPrct = notYetAllocated / TR;
// Logic: Check if the fraction of resources in
// miscResources is greater than the cap (ip.MISCPOOLSIZE).
// If yes, take the first resource from miscResources
// and put it in one of the big pools, chosen at random.
// If the fraction of resources in miscResources is still
// greater than the cap, repeat the loop. Otherwise,
// stop and put the remaining resources in the last pool.
//
// Also stop under the following condition. Assume the head
// of the miscResources list is allocated. Is the value of the
// remaining resources in miscResources (the tail) greater than
// zero? If not, stop. There has to be at least one non-zero
// resource in the last pool.
while (
(miscPoolPrct > ip.MISCPOOLSIZE) &&
(miscResources.Skip(1).Aggregate(0.0, (acc, indx) => acc + RCC[indx]) > 0.0)
)
{
// Pick a pool at random to get the next resource
int poolIndx = (int)GenRandNumbers.GenUniformInt(0, a - 2);
B[poolIndx].Add(miscResources.First());
miscResources.RemoveAt(0);
notYetAllocated = miscResources.Aggregate(0.0, (acc, indx) => acc + RCC[indx]);
miscPoolPrct = notYetAllocated / TR;
}
B.Last().AddRange(miscResources);
#endregion
}
// p == 3:
// Seed the first pool with the largest resource.
// Iterate over the other pools. For each pool, select a seed resource:
// This is the largest of the remaining, unassigned resources, and
// assign it to the pool.
// Form a correlation vector (a list), which is the correlation
// of each resource in remainingResources with the seed resource.
// If the highest correlation is greater than ip.CC, there are
// enough remaining resources to fill the remaining pools, and
// satisfy the constraint about the miscellaneous pool size,
//assign resource with the highest correlation to the current pool.
// Once there are just as many resources remaining as there are pools,
// assign one resource to each remaining pool.
else if (p == 3)
{
#region Flowchart 6.4
// Initialize B
for (int i = 0; i < B.Length; ++i)
{
B[i] = new List <int>();
}
// Seed the first pool with the largest resource
B[0].Add(RANK[0]);
List <int> remainingResources = RANK.Skip(1).ToList();
// Assign all zero resources to the last (miscellaneous) pool.
// That way, each of the remaining pools is guaranteed to have
// a nonzero resource.
// This only works if there are at least as many nonzero resources
// as there are pools. If not, then skip this step so that each
// pool has at least one resource.
int numZeroResources = remainingResources.Count(res => RCC[res] == 0.0);
if (RCC.Dimension - numZeroResources >= B.Length)
{
while (RCC[remainingResources.Last()] == 0.0)
{
B.Last().Add(remainingResources.Last());
remainingResources.RemoveAt(remainingResources.Count - 1);
}
}
// Iterate over the pools. For each pool, select a seed resource,
// which is the first resource assigned to the pool.
// Form a correlation vector (a list), which is the correlation
// of each resource in remainingResources with the seed resource.
// While max of the list is greater than ip.CC, and while
// the other conditions are satisfied, assign resource with the
// maximum correlation to the current pool.
// Once condition 2 is no longer true, there are just as many
// resources remaining as there are pools. The loop then assigns
// one resource to each remaining pool.
// Once condition 3 is no longer true, it assigns one resource
// to each pool, and all the remaining resources to the last pool.
for (int currentPool = 0; currentPool < B.Length - 1; ++currentPool)
{
int seedResource = B[currentPool].First();
int poolsToBeFilled = B.Length - (currentPool + 1);
List <double> correlations = remainingResources.Select(res => CORR[res, seedResource]).ToList();
bool cond1 = correlations.Max() > ip.CC;
bool cond2 = remainingResources.Count > poolsToBeFilled;
// Magnitude of resources not yet allocated
double notYetAllocated = remainingResources.Aggregate(0.0, (acc, indx) => acc + RCC[indx]);
// Fraction of resources not yet allocated
double TR = RCC.Sum();
double miscPoolPrct = notYetAllocated / TR;
bool cond3 = miscPoolPrct > ip.MISCPOOLSIZE;
while (cond1 && cond2 && cond3)
{
// Find the index of the resource with the maximum correlation
// with the seed resource
double maxCorr = correlations.Max();
int maxCorrIndx = remainingResources[correlations.IndexOf(maxCorr)];
// Add it to the current pool
B[currentPool].Add(maxCorrIndx);
// Remove it from the remainingResources list
remainingResources.RemoveAt(correlations.IndexOf(maxCorr));
correlations.Remove(maxCorr);
// Recompute loop termination conditions
cond1 = correlations.Max() > ip.CC;
cond2 = remainingResources.Count > poolsToBeFilled;
notYetAllocated = remainingResources.Aggregate(0.0, (acc, indx) => acc + RCC[indx]);
miscPoolPrct = notYetAllocated / TR;
cond3 = miscPoolPrct > ip.MISCPOOLSIZE;
}
B[currentPool + 1].Add(remainingResources[0]);
remainingResources.RemoveAt(0);
}
B.Last().AddRange(remainingResources);
#endregion
}
else
{
throw new ApplicationException("Invalid value of p.");
}
}
else
{
#region Flowchart 6.5
B = new List <int>[] { new List <int>(RANK) };
#endregion
}
// The fraction of RCC that is in the miscellaneous (last)
// activity cost pool.
double miscPoolSize = B.Last().Aggregate(0.0, (acc, i) => acc + RCC[i]) / RCC.Sum();
#region Flowchart 6.5 -- Choosing drivers
// For each element of B, which is a list of resource indexes,
// sort it in descending order by pool size (RCC[element]).
// Technically, this is unnecessary, since elements should have
// been added to the lists in B in descending order. But instead
// of assuming that, since that could change in the future,
// I am going to re-sort. Heck, it's only one line of code,
// plus this essay of a comment that I just wrote.
{
var query = B.Select(list => list.OrderByDescending(indx => RCC[indx]));
int numToTake;
if (r == 0)
{
numToTake = 1;
}
else if (r == 1)
{
numToTake = ip.NUM;
}
else
{
throw new ApplicationException("Invalid value of r in FalseSys.cs.");
}
// This iterates over every list in query, and replaces that list
// with a list containing only the first numToTake elements.
var drivers = query.Select(list => list.Take(numToTake).ToList());
D = drivers.ToArray();
}
#endregion
}
/// <summary>
/// Randomly generates a firm object (production technology and output market parameters).
/// </summary>
/// <param name="ip">A pointer to the collection of input parameters.</param>
/// <param name="FirmID">Unique identifier for this firm (run number)</param>
public Firm(InputParameters ip, int FirmID)
{
// Choose random values for DISP2 (the top DISP1 resources
// account for DISP2 percent of total resource costs), and
// density (sparsity) of resource consumption pattern matrix
this.g = GenRandNumbers.GenUniformDbl(ip.DISP2_MIN, ip.DISP2_MAX);
this.d = GenRandNumbers.GenUniformDbl(ip.DNS_MIN, ip.DNS_MAX);
// Generate the true product margins and the true, optimal
// decision vector. Keep generating new margins until there
// is at least one product in the optimal mix.
RowVector MAR, DECT0;
do
{
MAR = this.GenMargins(ip);
DECT0 = MAR.Map(x => (x < 1.0) ? 0.0 : 1.0);
} while (DECT0.TrueForAll(x => x == 0.0));
// Generate vector of maximum production quantities
this.mxq = this.GenMXQ(ip);
// And associated vector of optimal production quantities
ColumnVector QT = mxq.ewMultiply(DECT0);
// Flowchart 5.1 - Create resource consumption pattern matrix
this.res_cons_pat = GenResConsPat(ip);
// Flowchart 5.2 - Compute TRU
// Calculate vector of total units of resource
// consumption, by product
ColumnVector TRU = this.CalcResConsumption(QT);
// Flowchart 5.3 - Compute MAXRU
// Calculate resource consumption under the assumption
// that all products are produced at maximum quantity
ColumnVector MAXRU = this.CalcResConsumption(mxq);
RowVector RCC, PC_B, RCCN;
double TCT0;
#region Flowchart 5.4 - Generate RCC, RCU, and RCCN
/* -------------------------------- */
// Flowchart 5.4(a)-(g)
// Generate vector of total resource costs (RCC)
RCC = GenRCC(ip);
/* -------------------------------- */
// Flowchart 5.4(h)
// Now generate unit resource costs (RCU) by doing element-wise
// division of RCC by MAXRU
this.rcu = RCC.Map((x, i) => x / MAXRU[i]);
/* -------------------------------- */
// Flowchart 5.4(i)
// Compute new RCC vector (RCCN) based on unit resource
// costs (RCU) and true unit resource consumption (TRU)
RCCN = this.rcu.ewMultiply(TRU);
// Check to see if the first resource (RCCN[0]) is the largest.
// If not, increase RCU[0] by just enough to make it so.
if (RCCN[0] < RCCN.Skip(1).Max() + 1)
{
RCCN[0] = Math.Ceiling(RCCN.Max()) + 1.0;
this.rcu[0] = RCCN[0] / TRU[0];
}
#endregion
// Flowchart 5.5 - Calculate PC_B
// Calculate true unit product costs
PC_B = this.CalcTrueProductCosts();
// Flowchart 5.6 - Compute total costs TCT0
// Compute total costs
TCT0 = this.CalcTotCosts(QT);
// Flowchart 5.7 - Rename RCCN to RCC
RCC = RCCN;
initial_rcc = RCC;
#region Flowchart 5.8 - Calculate SP, TRV0, PROFITT0
// Calculate product selling prices, total revenue, and profit
this.sp = PC_B.ewMultiply(MAR);
double TRV0 = this.sp * QT;
this.profitt0 = TRV0 - TCT0;
#endregion
// 5.9(a) Create RANK vector
// Note: this method provides a stable sort. It's important to use a stable sort.
// LOOKUP IN VERSION.TXT WHY IT'S IMPORTANT TO USE A STABLE SORT HERE.
initial_rank = Enumerable.Range(0, RCC.Dimension).OrderByDescending(i => RCC[i]).ToArray();
#region Flowchart 5.9(b) - Create RES_CONS_PAT_PRCT
this.res_cons_pat_prct = new RectangularMatrix(ip.RCP, ip.CO);
for (int r = 0; r < this.res_cons_pat.RowCount; ++r)
{
RowVector rv = this.res_cons_pat.Row(r);
if (TRU[r] != 0.0)
{
rv = rv.Map((alt_ij, col) => alt_ij * QT[col] / TRU[r]);
if (Math.Abs(rv.Sum() - 1.0) > 0.01)
{
throw new ApplicationException("Sum of row of RES_CONS_PAT_PRCT not equal to 1.");
}
}
else
{
rv = rv.Map(alt_ij => 0.0);
}
this.res_cons_pat_prct.CopyRowInto(rv, r);
}
#endregion
#region Flowchart 5.9(c) - Create correlation matrix
// Create correlation matrix for rows of RES_CONS_PAT_PRCT
MultivariateSample mvs = new MultivariateSample(ip.RCP);
for (int c = 0; c < this.res_cons_pat_prct.ColumnCount; ++c)
{
mvs.Add(this.res_cons_pat_prct.Column(c));
}
this.pearsoncorr = new SymmetricMatrix(ip.RCP);
for (int i = 0; i < mvs.Dimension; ++i)
{
for (int j = i; j < mvs.Dimension; ++j)
{
//PearsonCorr[i, j] = mvs.PearsonRTest( i, j ).Statistic;
this.pearsoncorr[i, j] = mvs.TwoColumns(i, j).PearsonRTest().Statistic;
}
}
#endregion
// Flowchart 5.10 - Logging true system
// Note: I'm deliberately passing copies of the fields MXQ, SP, etc.
Output.LogFirm(
ip, this, FirmID,
MAR, DECT0,
TRV0, TCT0, profitt0,
RCC);
}
